Leverage the power of PyTorch Geometric to develop and train custom Graph Neural Networks for your application

High-performance data retrieval from Neo4j with Apache Arrow

Image available under CC-BY-SA license on https://looneytunes.fandom.com/.

Combine web scraping, OCR, and entity recognition to construct and analyze the Matrix interaction network in Neo4j


This blog post will present how to combine web scraping, OCR…

Integrate PyKEEN library with Neo4j for multi-class link prediction using knowledge graph embedding models

Integrate SigmaJS network visualizations with GRAND stack (GraphQL, React, Apollo, Neo4j)

Airport routes visualized with the SigmaJS. Image by author.

Hands-on Tutorials

Learn how to combine OCR, named entity linking, relation extraction and external enrichment databases to construct a biomedical knowledge graph

Learn how you can use correlation between stock prices to infer a similarity network between stocks — and then use that network information to help you diversify your portfolio

Learn how to train and optimize Link Prediction models in the Neo4j Graph Data Science library to get the best results

Tomaz Bratanic

Data explorer. Turn everything into a graph. Author of Graph algorithms for Data Science at Manning publication.

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